Missing data imputation
Demographics | Physical health | Hearing | Cognition | Mobility and balance | Quality of life | Mental health | Social participation and support | Views on hearing loss |
Background
Why impute missing data?
Logistic regression and other statistical methods require complete cases. In our case, with 40+ variables of interest, dropping participants with any missing values leads to a sample size of 200+ cases instead of 500+. There is loss of power, and estimates from models will likely be biased. The goal of missing data imputation is to restore variance of the sample to make it better reflect characteristics of the population (i.e., give accurate estimates of standard errors, CI’s, and p-values).
MICE procedure
‘Multiple Imputation by Chained Equations’
Say there are three variables ‘A’, ‘B’, and ‘C’, each with some missing values. Choose variable ‘A’ to start filling in. Fill in missing values in ‘B’ and ‘C’ with temporary values, such as the mean.
Make an equation A ~ B + C, using observed cases of ‘A’ to predict missing values of ‘A’, including a random component. Move on to predicting missing ‘B’, using B ~ A + C and including predicted ‘A’, again including a random component. Move on to predicting missing ‘C’, using C ~ A + B and predicted ‘A’ and ‘B’. This is one cycle.
Choose the number of cycles, say 10 iterations. At the end of 10 iterations, an “imputed” dataset is formed with no missing values. Choose the number of imputed datasets to form (the same analysis will be conducted on each slightly different dataset, and the results will be pooled). Choose which variables should be used as predictors of other variables. Choose which method to use for predicting missing values, e.g., predictive mean matching. For derived variables such as summed scores, consider whether to impute components first and then calculate derived scores, or impute derived scores. Consider whether there should be an order of which variables to start imputing first.
Check whether the imputed data “converge” (the means and SEs stabilize after a few iterations, and are similar across imputed datasets). Check the distributions and characteristics of imputed data (e.g. integer-only values, floors and ceilings, plausibility), and their similarity to observed data.
1. Pre-imputation work
(i) Evaluate missingness
Variables of interest
Demographics: Age, Gender, Work, Volunteer, Live alonePhysical health: Rating, Multimorbidity score, Subjective vision (loss, rating aided), Subjective hearing (loss, rating aided, rating unaided)
Hearing health: Hearing device use, Hearing device type, Tinnitus past 7 days, 15i-SSQ mean score, SIM mean score, EmoCheQ mean score, HHIE-S total score, BPTA4
Cognitive health: Subjective cognitive impairment, CSRQ mean score
Mobility and balance: Mobility aid use, ABC (balance confidence) mean score
Quality of life: SWLS mean score, WHO overall QoL, WHO health QoL, WHO money, WHO four domains
Mental health: PHQ4, split into anxiety and depression subscores
Social factors: Loneliness, Social Network Index, Social Participation Frequency, Social Participation Types, Social Support MOS mean score
Views: Connections total correct score, Motivations mean score
% Missing data within participants
##
## The decimal point is at the |
##
## 0 | 00004444444444444444444444444444444444444999999999999999999999999999+193
## 2 | 22222222222222222222222222222222222222222277777777777777777777777777+16
## 4 | 000044444999993333333888888888888
## 6 | 222222222222222666666666666666666111111111111111111155555555555
## 8 | 0000000004444888833337777
## 10 | 221199
## 12 | 488
## 14 | 2055
## 16 | 47
## 18 | 65
## 20 |
## 22 | 5
## 24 | 2
## 26 |
## 28 |
## 30 |
## 32 |
## 34 |
## 36 |
## 38 |
## 40 |
## 42 | 9
## 44 |
## 46 |
## 48 |
## 50 |
## 52 |
## 54 |
## 56 |
## 58 |
## 60 | 6
## 62 |
## 64 | 6
## 66 | 87
## 68 |
## 70 | 8827
## 72 | 6
## 74 | 337
## 76 | 0
## 78 |
## 80 | 5
## 82 |
## 84 |
## 86 |
## 88 |
## 90 | 6
## 92 |
## 94 |
## 96 |
## 98 | 66Missing data patterns
Participants with <26% missing data (n=509): 
Participants with >42% missing data (n=18): 
(ii) Data cleaning
Rules
- For “single-item” variables (e.g. loneliness): NA’s are left as
is.
- For co-morbidity checklist: All responses other than “yes” (NA’s,
No, Don’t know) are treated as “no”.
- For composite variables: If a participant has “NA” for all items,
the composite score is also “NA”.
- WHOQOL-BREF: Follow their protocol for NA’s.
- For SIM, EmoCheQ, CSRQ, PHQ4, Views on motivations: Impute case
mean.
- For 15i-SSQ: Impute case mean within subscale.
- For HHIES: Impute case mode within subscale.
- For ABC: Recode NA’s to 0 (single participant).
- For Social Network Index: Recode NA’s to “never”.
- For Social Participation: Recode NA’s to “never”.
- For Social Support: Recode NA’s to “none”.
- For Views (Connections): Drop foil item; only correct items
credited.
- For Views (Motivations): Impute mean.
(iii) Evaluate missingness again
% Missing data within participants
##
## The decimal point is at the |
##
## 0 | 00000000000000000000000000000000000000000000000000000000000000000000+151
## 2 | 22222222222222222222222222222222222222222222222222222222222222222222+51
## 4 | 333333333333333333333333333333333333333333333
## 6 | 555555555555555555555555555555555555555555555555555555555
## 8 | 777777777777777777777777777
## 10 | 99999999999
## 12 | 00000
## 14 |
## 16 | 4
## 18 | 6
## 20 |
## 22 |
## 24 |
## 26 |
## 28 |
## 30 |
## 32 |
## 34 |
## 36 |
## 38 |
## 40 | 3
## 42 |
## 44 |
## 46 |
## 48 |
## 50 | 0
## 52 | 22
## 54 | 3
## 56 |
## 58 | 7777
## 60 | 999
## 62 |
## 64 | 2
## 66 |
## 68 | 6
## 70 | 7
## 72 |
## 74 |
## 76 | 1
## 78 |
## 80 |
## 82 |
## 84 |
## 86 |
## 88 |
## 90 | 33Missing data patterns
Participants with <20% missing data (n=509):
## # A tibble: 45 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 Gender_bin 0 0
## 2 Age 2 0.393
## 3 Retired_bin 0 0
## 4 Volunteer 0 0
## 5 Lives_alone_bin 0 0
## 6 Phys_health_rating 7 1.38
## 7 Multimorbidity_score 0 0
## 8 Subj_vision_loss_bin 18 3.54
## 9 Subj_vision_rating_aided 1 0.196
## 10 Subj_hearing_loss_bin 36 7.07
## 11 any_hearing_device 0 0
## 12 study2_HA 0 0
## 13 Subj_hearing_rating_aided_REV 159 31.2
## 14 Subj_hearing_rating_unaided_REV 8 1.57
## 15 Tinnitus_past_wk_bin 0 0
## 16 ssq_speech_REV 46 9.04
## 17 ssq_spatial_REV 51 10.0
## 18 ssq_qualities_REV 3 0.589
## 19 SIM_mean 12 2.36
## 20 Emocheq_mean 8 1.57
## 21 hhies_emo_total 0 0
## 22 hhies_soc_total 0 0
## 23 positive_SCI_bin 0 0
## 24 CSRQ_mean 0 0
## 25 Mobility_needs_bin 0 0
## 26 ABC_mean 0 0
## 27 SWLS_mean 0 0
## 28 WHOQOL_overall_qol 0 0
## 29 WHOQOL_health_qol 0 0
## 30 WHOQOL_Dom1_phys 0 0
## 31 WHOQOL_Dom2_psy 0 0
## 32 WHOQOL_Dom3_soc 1 0.196
## 33 WHOQOL_Dom4_env 0 0
## 34 WHO_money 0 0
## 35 PHQ4_anx_sum 1 0.196
## 36 PHQ4_dep_sum 1 0.196
## 37 Lonely_bin 1 0.196
## 38 Social_network_index 1 0.196
## 39 Soc_part_freq 1 0.196
## 40 Soc_part_types 1 0.196
## 41 Socsupp_mean 5 0.982
## 42 Connections_total 9 1.77
## 43 Motivate_mean 5 0.982
## 44 study1_HA_bin 78 15.3
## 45 PTA4_better_ear 73 14.3Participants with >39%% missing data (n=18):
(iv) Justify discarding/retaining participants
Drop 2 cases that are fully missing
## Progress Duration.in.seconds Finished
## 458 0 217 0
## 467 1 540 0## # A tibble: 46 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 Gender_bin 2 100
## 2 Age 2 100
## 3 Retired_bin 2 100
## 4 Volunteer 2 100
## 5 Lives_alone_bin 2 100
## 6 Phys_health_rating 2 100
## 7 Multimorbidity_score 0 0
## 8 Subj_vision_loss_bin 2 100
## 9 Subj_vision_rating_aided 2 100
## 10 Subj_hearing_loss_bin 2 100
## 11 any_hearing_device 0 0
## 12 study2_HA 0 0
## 13 Subj_hearing_rating_aided_REV 2 100
## 14 Subj_hearing_rating_unaided_REV 2 100
## 15 Tinnitus_past_wk_bin 0 0
## 16 ssq_speech_REV 2 100
## 17 ssq_spatial_REV 2 100
## 18 ssq_qualities_REV 2 100
## 19 SIM_mean 2 100
## 20 Emocheq_mean 2 100
## 21 hhies_emo_total 2 100
## 22 hhies_soc_total 2 100
## 23 positive_SCI_bin 2 100
## 24 CSRQ_mean 2 100
## 25 Mobility_needs_bin 2 100
## 26 ABC_mean 2 100
## 27 SWLS_mean 2 100
## 28 WHOQOL_overall_qol 2 100
## 29 WHOQOL_health_qol 2 100
## 30 WHOQOL_Dom1_phys 2 100
## 31 WHOQOL_Dom2_psy 2 100
## 32 WHOQOL_Dom3_soc 2 100
## 33 WHOQOL_Dom4_env 2 100
## 34 WHO_money 2 100
## 35 PHQ4_anx_sum 2 100
## 36 PHQ4_dep_sum 2 100
## 37 Lonely_bin 2 100
## 38 Social_network_index 2 100
## 39 Soc_part_freq 2 100
## 40 Soc_part_types 2 100
## 41 Socsupp_mean 2 100
## 42 Connections_total 2 100
## 43 Motivate_mean 2 100
## 44 study1_HA_bin 2 100
## 45 PTA4_better_ear 2 100
## 46 PTA4_asym 2 100Retain 16 that mostly have age, audiogram, earlier measures
## Progress Duration.in.seconds Finished
## 45 58 413 0
## 77 19 247 0
## 136 58 308782 0
## 153 30 449 0
## 166 52 185 0
## 176 53 1693 0
## 187 53 518035 0
## 192 45 504174 0
## 228 13 96 0
## 246 64 1719 0
## 318 55 466 0
## 364 55 988 0
## 405 55 650 0
## 483 45 731 0
## 520 64 6724 0
## 522 70 2376 0## # A tibble: 46 × 3
## variable n_miss pct_miss
## <chr> <int> <num>
## 1 Gender_bin 0 0
## 2 Age 1 6.25
## 3 Retired_bin 0 0
## 4 Volunteer 0 0
## 5 Lives_alone_bin 0 0
## 6 Phys_health_rating 2 12.5
## 7 Multimorbidity_score 0 0
## 8 Subj_vision_loss_bin 2 12.5
## 9 Subj_vision_rating_aided 2 12.5
## 10 Subj_hearing_loss_bin 3 18.8
## 11 any_hearing_device 0 0
## 12 study2_HA 0 0
## 13 Subj_hearing_rating_aided_REV 8 50
## 14 Subj_hearing_rating_unaided_REV 3 18.8
## 15 Tinnitus_past_wk_bin 0 0
## 16 ssq_speech_REV 13 81.2
## 17 ssq_spatial_REV 11 68.8
## 18 ssq_qualities_REV 6 37.5
## 19 SIM_mean 11 68.8
## 20 Emocheq_mean 11 68.8
## 21 hhies_emo_total 13 81.2
## 22 hhies_soc_total 13 81.2
## 23 positive_SCI_bin 13 81.2
## 24 CSRQ_mean 15 93.8
## 25 Mobility_needs_bin 15 93.8
## 26 ABC_mean 15 93.8
## 27 SWLS_mean 15 93.8
## 28 WHOQOL_overall_qol 16 100
## 29 WHOQOL_health_qol 16 100
## 30 WHOQOL_Dom1_phys 16 100
## 31 WHOQOL_Dom2_psy 16 100
## 32 WHOQOL_Dom3_soc 16 100
## 33 WHOQOL_Dom4_env 16 100
## 34 WHO_money 16 100
## 35 PHQ4_anx_sum 16 100
## 36 PHQ4_dep_sum 16 100
## 37 Lonely_bin 16 100
## 38 Social_network_index 16 100
## 39 Soc_part_freq 16 100
## 40 Soc_part_types 16 100
## 41 Socsupp_mean 16 100
## 42 Connections_total 16 100
## 43 Motivate_mean 16 100
## 44 study1_HA_bin 3 18.8
## 45 PTA4_better_ear 3 18.8
## 46 PTA4_asym 3 18.8(v) Variable relationships
Correlations heatmap: Hearing
Correlations heatmap: Physical health
PCA
Note: PC1 and PC2 account for 36% of the total variance.
2. Imputation using MICE
Current method
- Use predictors that correlate 0.5 or better to impute missing data
in a variable (30 variables); if no such predictors, adjust threshold to
0.4 (3 variables), then 0.3, then 0.2 (2 variables)
pdf
- Eight variables are complete and do not require imputing; 2
variables have no predictors that correlate at least r = 0.2
(Subj_vision_loss_bin, Connections_total)
- MICE settings: total of 5 imputed datasets, with a maximum of 10 iterations per dataset, using predictive means matching to impute missing values
Check imputed data
PCA with standardized imputed data
PCA
Note: This is only 1 of 5 imputed datasets, but the plots are similar.
3. Predicting hearing aid adoption
Complete cases vs. imputed data
Note: All participants together; not filtered by hearing aid candidacy.
Regression output (complete cases, n=346)
Non-hearing aid users = 267
Hearing aid users = 79 (22.8%)
Note: Dropped Subj_hearing_rating_aided_REV & SWLS_mean due to VIF
> 5
## Term Estimate StdError z p OddsRatio CIlower CIupper
## 1 (Intercept) -24.2964 884.2360 -0.0275 0.9781 0.0000 0.0000 Inf
## 2 Gender_bin 0.5265 0.4564 1.1536 0.2487 1.6930 0.6921 4.1418
## 3 Age -0.0185 0.0346 -0.5336 0.5936 0.9817 0.9172 1.0506
## 4 Retired_bin 0.0571 0.5098 0.1121 0.9108 1.0588 0.3898 2.8757
## 5 Volunteer_rec 0.5477 0.2816 1.9448 0.0518 1.7293 0.9957 3.0031
## 6 Lives_alone_bin -0.2751 0.5566 -0.4943 0.6211 0.7595 0.2551 2.2608
## 7 Phys_health_rating 0.0966 0.3728 0.2590 0.7956 1.1014 0.5304 2.2868
## 8 Multimorbidity_score -0.0199 0.1206 -0.1652 0.8688 0.9803 0.7739 1.2417
## 9 Mobility_needs_bin -0.3204 1.1148 -0.2874 0.7738 0.7258 0.0816 6.4536
## 10 ABC_mean -0.0315 0.0261 -1.2055 0.2280 0.9690 0.9206 1.0199
## 11 Subj_vision_rating_aided 0.0508 0.2960 0.1717 0.8637 1.0521 0.5890 1.8795
## 12 Subj_hearing_loss_bin 17.0709 884.2210 0.0193 0.9846 25929968.0135 0.0000 Inf
## 13 Subj_hearing_rating_unaided_REV 1.0591 0.3850 2.7506 0.0059 2.8837 1.3559 6.1334
## 14 Tinnitus_past_wk_bin 0.1555 0.4104 0.3790 0.7047 1.1683 0.5227 2.6112
## 15 PTA4_better_ear 0.1214 0.0288 4.2225 0.0000 1.1291 1.0672 1.1945
## 16 PTA4_asym 0.0472 0.0153 3.0891 0.0020 1.0483 1.0174 1.0802
## 17 SSQ15i_mean_REV -0.6680 0.1855 -3.6002 0.0003 0.5128 0.3564 0.7376
## 18 Emocheq_mean -0.0308 0.2780 -0.1108 0.9118 0.9697 0.5623 1.6721
## 19 HHIES_total 0.0596 0.0386 1.5445 0.1225 1.0614 0.9841 1.1448
## 20 SIM_mean -0.1358 0.1165 -1.1662 0.2435 0.8730 0.6948 1.0968
## 21 positive_SCI_bin 1.1976 0.7118 1.6824 0.0925 3.3122 0.8207 13.3674
## 22 CSRQ_mean -0.1344 0.6195 -0.2170 0.8282 0.8742 0.2596 2.9440
## 23 PHQ4_anx_sum 0.7501 0.2500 3.0009 0.0027 2.1173 1.2972 3.4559
## 24 PHQ4_dep_sum -0.5725 0.3340 -1.7137 0.0866 0.5641 0.2931 1.0857
## 25 WHOQOL_overall_qol -0.4355 0.4717 -0.9233 0.3558 0.6469 0.2567 1.6306
## 26 WHOQOL_health_qol 0.3760 0.3228 1.1648 0.2441 1.4565 0.7736 2.7421
## 27 WHO_money 0.8039 0.2691 2.9869 0.0028 2.2343 1.3184 3.7865
## 28 Socsupp_mean 0.2161 0.2994 0.7216 0.4705 1.2412 0.6902 2.2320
## 29 Social_network_index -0.1362 0.1756 -0.7754 0.4381 0.8727 0.6185 1.2313
## 30 Soc_part_freq -0.2681 0.3671 -0.7303 0.4652 0.7648 0.3724 1.5706
## 31 Soc_part_types 0.0183 0.1582 0.1155 0.9080 1.0184 0.7469 1.3886
## 32 Lonely_bin -0.2511 0.6864 -0.3658 0.7145 0.7780 0.2026 2.9868
## 33 Motivate_mean 0.3051 0.2395 1.2743 0.2026 1.3568 0.8486 2.1694Regression output (imputed data, n=525)
## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -0.6403 0.3616 -1.7705 234.2875 0.0779 0.5271 0.2595 1.0708
## 2 Gender_bin 0.0567 0.0364 1.5575 471.1834 0.1200 1.0583 0.9855 1.1366
## 3 Age 0.0025 0.0025 0.9825 369.2798 0.3265 1.0025 0.9976 1.0074
## 4 Retired_bin -0.0293 0.0369 -0.7938 487.6629 0.4277 0.9711 0.9034 1.0440
## 5 Volunteer_rec 0.0426 0.0207 2.0563 446.2648 0.0403 1.0435 1.0020 1.0867
## 6 Lives_alone_bin -0.0218 0.0421 -0.5181 456.7222 0.6047 0.9784 0.9009 1.0626
## 7 Phys_health_rating -0.0025 0.0275 -0.0922 277.7467 0.9266 0.9975 0.9452 1.0527
## 8 Multimorbidity_score 0.0044 0.0077 0.5739 482.4389 0.5663 1.0044 0.9894 1.0197
## 9 Mobility_needs_bin -0.0263 0.0882 -0.2982 197.5034 0.7658 0.9740 0.8194 1.1579
## 10 ABC_mean -0.0032 0.0017 -1.9082 333.4289 0.0572 0.9968 0.9935 1.0001
## 11 Subj_vision_rating_aided 0.0101 0.0234 0.4302 464.5342 0.6672 1.0102 0.9649 1.0576
## 12 Subj_hearing_loss_bin 0.0965 0.0509 1.8948 251.8043 0.0593 1.1013 0.9967 1.2168
## 13 Subj_hearing_rating_unaided_REV 0.0970 0.0253 3.8375 474.5172 0.0001 1.1019 1.0486 1.1579
## 14 Tinnitus_past_wk_bin -0.0538 0.0348 -1.5461 477.2992 0.1227 0.9476 0.8851 1.0145
## 15 PTA4_better_ear 0.0077 0.0023 3.2957 65.6229 0.0016 1.0077 1.0032 1.0123
## 16 PTA4_asym 0.0028 0.0015 1.8521 97.2075 0.0670 1.0028 0.9999 1.0058
## 17 SSQ15i_mean_REV -0.0682 0.0134 -5.0841 442.5085 0.0000 0.9341 0.9099 0.9589
## 18 Emocheq_mean -0.0047 0.0218 -0.2154 308.9247 0.8296 0.9953 0.9537 1.0388
## 19 HHIES_total 0.0063 0.0031 2.0680 139.2159 0.0405 1.0063 1.0002 1.0125
## 20 SIM_mean -0.0037 0.0086 -0.4296 151.3338 0.6681 0.9963 0.9797 1.0132
## 21 positive_SCI_bin 0.0444 0.0597 0.7437 235.7357 0.4578 1.0454 0.9300 1.1752
## 22 CSRQ_mean -0.0471 0.0504 -0.9332 237.7601 0.3517 0.9540 0.8643 1.0530
## 23 PHQ4_anx_sum 0.0590 0.0189 3.1289 349.5162 0.0019 1.0608 1.0222 1.1008
## 24 PHQ4_dep_sum -0.0048 0.0219 -0.2174 410.0640 0.8280 0.9952 0.9534 1.0389
## 25 WHOQOL_overall_qol 0.0215 0.0338 0.6349 399.5565 0.5258 1.0217 0.9562 1.0917
## 26 WHOQOL_health_qol 0.0263 0.0239 1.0977 242.7875 0.2734 1.0266 0.9797 1.0759
## 27 WHO_money 0.0327 0.0191 1.7141 379.8742 0.0873 1.0332 0.9953 1.0727
## 28 Socsupp_mean 0.0121 0.0242 0.5018 257.1651 0.6163 1.0122 0.9653 1.0613
## 29 Social_network_index -0.0035 0.0143 -0.2440 257.7509 0.8074 0.9965 0.9690 1.0248
## 30 Soc_part_freq 0.0044 0.0285 0.1553 277.8290 0.8767 1.0044 0.9498 1.0621
## 31 Soc_part_types -0.0052 0.0132 -0.3953 230.6520 0.6930 0.9948 0.9694 1.0209
## 32 Lonely_bin -0.0036 0.0491 -0.0739 243.8208 0.9412 0.9964 0.9050 1.0971
## 33 Motivate_mean 0.0172 0.0208 0.8254 197.5883 0.4101 1.0173 0.9767 1.0597Legend: Asterisks denote p < 0.05; crosses denote p [0.05, 0.1]
Accuracy of model predictions
Note: Not really a fair comparison as models and model coefficients are different between complete-cases and imputed data.
## [1] "Complete cases, using median as boundary"## predicted
## actual 0 1
## 0 170 97
## 1 3 76## [1] "Accuracy: 0.711"## [1] "Sensitivity: 0.962"## [1] "Specificity: 0.637"
## [1] "Imputed data, using median as boundary"## predicted
## actual 0 1
## 0 255 167
## 1 8 95## [1] "Accuracy: 0.667"## [1] "Sensitivity: 0.922"## [1] "Specificity: 0.604"Grouping by HHIE-S status
Counts
0-8 no handicap, 10-24 mild to moderate, 26-40 severe
## HHIES
## UseHA None MildMod Sev <NA>
## 0 233 148 30 11
## 1 26 62 13 2
## <NA> 0 0 0 0## [1] 0.100 0.295 0.302 0.154Regression output (imputed data, n=525)
## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) 0.1962 0.4650 0.4219 183.5297 0.6736 1.2168 0.4891 3.0271
## 2 Gender_bin -0.0326 0.0425 -0.7671 223.1006 0.4438 0.9679 0.8906 1.0520
## 3 Age -0.0003 0.0030 -0.0861 195.9337 0.9315 0.9997 0.9938 1.0056
## 4 Retired_bin -0.0200 0.0414 -0.4817 220.3576 0.6305 0.9802 0.9038 1.0631
## 5 Volunteer_rec 0.0331 0.0231 1.4306 220.6900 0.1540 1.0337 0.9879 1.0815
## 6 Lives_alone_bin 0.0398 0.0462 0.8608 221.0689 0.3903 1.0406 0.9505 1.1392
## 7 Phys_health_rating -0.0295 0.0316 -0.9348 215.7359 0.3510 0.9709 0.9126 1.0330
## 8 Multimorbidity_score 0.0100 0.0112 0.8962 221.7392 0.3711 1.0101 0.9881 1.0325
## 9 Mobility_needs_bin 0.0198 0.1146 0.1728 214.7225 0.8630 1.0200 0.8148 1.2769
## 10 ABC_mean -0.0013 0.0026 -0.5184 223.0057 0.6047 0.9987 0.9936 1.0038
## 11 Subj_vision_rating_aided -0.0231 0.0283 -0.8162 218.0165 0.4153 0.9772 0.9244 1.0329
## 12 Subj_hearing_loss_bin 0.0905 0.0500 1.8105 221.0717 0.0716 1.0947 0.9925 1.2074
## 13 Subj_hearing_rating_unaided_REV 0.0481 0.0293 1.6414 202.2892 0.1023 1.0493 0.9907 1.1113
## 14 Tinnitus_past_wk_bin -0.0516 0.0426 -1.2121 221.3916 0.2268 0.9497 0.8736 1.0324
## 15 PTA4_better_ear 0.0096 0.0029 3.3415 105.5930 0.0012 1.0096 1.0039 1.0154
## 16 PTA4_asym 0.0043 0.0033 1.2813 29.2730 0.2101 1.0043 0.9978 1.0108
## 17 SSQ15i_mean_REV -0.0507 0.0202 -2.5136 138.4644 0.0131 0.9506 0.9137 0.9890
## 18 Emocheq_mean -0.0076 0.0287 -0.2650 220.7188 0.7912 0.9924 0.9381 1.0499
## 19 HHIES_total 0.0042 0.0075 0.5613 219.0136 0.5752 1.0042 0.9896 1.0191
## 20 SIM_mean 0.0027 0.0094 0.2892 204.2855 0.7727 1.0027 0.9844 1.0213
## 21 positive_SCI_bin 0.1466 0.1061 1.3813 179.7737 0.1689 1.1579 0.9405 1.4255
## 22 CSRQ_mean -0.0401 0.0542 -0.7396 220.0602 0.4604 0.9607 0.8639 1.0684
## 23 PHQ4_anx_sum 0.0506 0.0232 2.1797 215.4355 0.0304 1.0519 1.0051 1.1008
## 24 PHQ4_dep_sum -0.0408 0.0310 -1.3165 190.7873 0.1896 0.9600 0.9034 1.0202
## 25 WHOQOL_overall_qol -0.0135 0.0396 -0.3407 171.3142 0.7337 0.9866 0.9129 1.0662
## 26 WHOQOL_health_qol 0.0028 0.0274 0.1014 202.5631 0.9194 1.0028 0.9504 1.0581
## 27 WHO_money 0.0439 0.0236 1.8571 222.3120 0.0646 1.0449 0.9976 1.0943
## 28 Socsupp_mean 0.0170 0.0288 0.5880 215.9515 0.5571 1.0171 0.9613 1.0762
## 29 Social_network_index -0.0099 0.0154 -0.6473 222.8188 0.5181 0.9901 0.9607 1.0205
## 30 Soc_part_freq -0.0143 0.0339 -0.4212 196.6811 0.6741 0.9858 0.9224 1.0535
## 31 Soc_part_types -0.0069 0.0142 -0.4865 211.1557 0.6271 0.9931 0.9659 1.0212
## 32 Lonely_bin -0.0189 0.0621 -0.3040 215.3301 0.7614 0.9813 0.8688 1.1083
## 33 Motivate_mean -0.0219 0.0236 -0.9279 218.4380 0.3545 0.9783 0.9341 1.0247## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -1.3733 0.5989 -2.2930 124.8454 0.0235 0.2533 0.0783 0.8192
## 2 Gender_bin 0.1154 0.0656 1.7607 190.4086 0.0799 1.1223 0.9869 1.2763
## 3 Age 0.0054 0.0045 1.2010 125.0713 0.2320 1.0054 0.9966 1.0143
## 4 Retired_bin -0.0564 0.0660 -0.8549 216.5146 0.3935 0.9452 0.8305 1.0757
## 5 Volunteer_rec 0.0408 0.0371 1.0988 217.2892 0.2731 1.0416 0.9686 1.1202
## 6 Lives_alone_bin -0.1349 0.0773 -1.7448 211.4367 0.0825 0.8738 0.7510 1.0167
## 7 Phys_health_rating 0.0197 0.0460 0.4289 210.2493 0.6684 1.0199 0.9320 1.1161
## 8 Multimorbidity_score 0.0002 0.0114 0.0206 208.7751 0.9836 1.0002 0.9781 1.0228
## 9 Mobility_needs_bin -0.0130 0.1352 -0.0960 112.4445 0.9237 0.9871 0.7573 1.2866
## 10 ABC_mean -0.0046 0.0023 -1.9717 197.9761 0.0500 0.9954 0.9909 0.9999
## 11 Subj_vision_rating_aided 0.0372 0.0383 0.9706 210.7444 0.3329 1.0379 0.9628 1.1188
## 12 Subj_hearing_loss_bin 0.0967 0.1113 0.8688 159.3392 0.3863 1.1015 0.8856 1.3701
## 13 Subj_hearing_rating_unaided_REV 0.1389 0.0459 3.0292 200.1503 0.0028 1.1490 1.0502 1.2572
## 14 Tinnitus_past_wk_bin -0.0386 0.0560 -0.6891 206.9787 0.4916 0.9621 0.8621 1.0738
## 15 PTA4_better_ear 0.0088 0.0040 2.2120 27.0475 0.0356 1.0088 1.0010 1.0168
## 16 PTA4_asym 0.0027 0.0022 1.2168 33.9089 0.2321 1.0027 0.9984 1.0070
## 17 SSQ15i_mean_REV -0.0734 0.0198 -3.7135 211.7069 0.0003 0.9292 0.8939 0.9660
## 18 Emocheq_mean 0.0082 0.0330 0.2473 214.0387 0.8049 1.0082 0.9451 1.0756
## 19 HHIES_total 0.0035 0.0054 0.6527 154.0751 0.5149 1.0035 0.9929 1.0142
## 20 SIM_mean -0.0196 0.0140 -1.4068 206.5296 0.1610 0.9806 0.9540 1.0079
## 21 positive_SCI_bin 0.0844 0.0836 1.0101 209.2780 0.3136 1.0881 0.9236 1.2818
## 22 CSRQ_mean -0.0339 0.0962 -0.3524 92.2837 0.7253 0.9667 0.8006 1.1673
## 23 PHQ4_anx_sum 0.0446 0.0314 1.4199 185.7922 0.1573 1.0456 0.9832 1.1120
## 24 PHQ4_dep_sum 0.0244 0.0330 0.7400 199.5112 0.4602 1.0247 0.9605 1.0932
## 25 WHOQOL_overall_qol 0.0633 0.0622 1.0167 118.1008 0.3114 1.0653 0.9431 1.2035
## 26 WHOQOL_health_qol 0.0390 0.0406 0.9619 206.9667 0.3372 1.0398 0.9602 1.1259
## 27 WHO_money 0.0225 0.0320 0.7029 109.8648 0.4836 1.0228 0.9606 1.0890
## 28 Socsupp_mean -0.0189 0.0403 -0.4681 167.3214 0.6403 0.9813 0.9068 1.0619
## 29 Social_network_index 0.0012 0.0244 0.0511 212.3747 0.9593 1.0012 0.9544 1.0502
## 30 Soc_part_freq 0.0246 0.0472 0.5210 142.3688 0.6032 1.0249 0.9343 1.1242
## 31 Soc_part_types -0.0020 0.0234 -0.0849 199.9804 0.9324 0.9980 0.9533 1.0448
## 32 Lonely_bin 0.0211 0.0788 0.2681 206.1755 0.7889 1.0213 0.8752 1.1919
## 33 Motivate_mean 0.0712 0.0364 1.9567 172.9059 0.0520 1.0738 0.9999 1.1532Legend: Asterisks denote p < 0.05; crosses denote p [0.05, 0.1]
Grouping by vision status
Counts
##
## 0 1 <NA>
## 215 290 20Regression output (imputed data, n=525)
## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -0.3066 0.5791 -0.5295 176.5355 0.5971 0.7359 0.2365 2.2897
## 2 Gender_bin 0.0271 0.0511 0.5301 174.6973 0.5967 1.0275 0.9295 1.1357
## 3 Age -0.0015 0.0040 -0.3808 133.1376 0.7039 0.9985 0.9907 1.0064
## 4 Retired_bin -0.0385 0.0539 -0.7141 178.9783 0.4761 0.9622 0.8658 1.0694
## 5 Volunteer_rec 0.0678 0.0296 2.2906 170.0660 0.0232 1.0702 1.0098 1.1341
## 6 Lives_alone_bin -0.1206 0.0628 -1.9213 177.4447 0.0563 0.8864 0.7837 1.0025
## 7 Phys_health_rating -0.0323 0.0401 -0.8052 175.6176 0.4218 0.9682 0.8950 1.0474
## 8 Multimorbidity_score 0.0166 0.0139 1.1934 179.3487 0.2343 1.0167 0.9894 1.0448
## 9 Mobility_needs_bin -0.0900 0.1325 -0.6796 178.8050 0.4976 0.9139 0.7049 1.1849
## 10 ABC_mean -0.0048 0.0033 -1.4297 178.4190 0.1545 0.9952 0.9888 1.0017
## 11 Subj_vision_rating_aided 0.0062 0.0366 0.1698 177.8689 0.8654 1.0062 0.9366 1.0811
## 12 Subj_hearing_loss_bin 0.0965 0.0744 1.2966 110.8065 0.1975 1.1013 0.9519 1.2742
## 13 Subj_hearing_rating_unaided_REV 0.0246 0.0383 0.6438 171.5901 0.5206 1.0249 0.9508 1.1048
## 14 Tinnitus_past_wk_bin -0.0340 0.0559 -0.6071 152.2968 0.5447 0.9666 0.8663 1.0785
## 15 PTA4_better_ear 0.0096 0.0039 2.4399 19.4762 0.0244 1.0096 1.0020 1.0174
## 16 PTA4_asym 0.0037 0.0021 1.8075 176.0733 0.0724 1.0037 0.9996 1.0078
## 17 SSQ15i_mean_REV -0.0512 0.0212 -2.4180 179.0185 0.0166 0.9501 0.9114 0.9904
## 18 Emocheq_mean 0.0014 0.0336 0.0404 157.1019 0.9678 1.0014 0.9376 1.0696
## 19 HHIES_total 0.0091 0.0046 1.9563 162.4779 0.0521 1.0091 1.0001 1.0183
## 20 SIM_mean 0.0042 0.0116 0.3646 176.8644 0.7158 1.0042 0.9816 1.0273
## 21 positive_SCI_bin -0.0876 0.0984 -0.8899 155.3114 0.3749 0.9161 0.7554 1.1110
## 22 CSRQ_mean -0.0522 0.0741 -0.7045 136.3395 0.4823 0.9491 0.8208 1.0975
## 23 PHQ4_anx_sum 0.0509 0.0274 1.8535 176.7850 0.0655 1.0522 0.9972 1.1103
## 24 PHQ4_dep_sum -0.0102 0.0361 -0.2822 165.1584 0.7782 0.9899 0.9222 1.0624
## 25 WHOQOL_overall_qol 0.0134 0.0509 0.2627 179.1511 0.7931 1.0135 0.9173 1.1198
## 26 WHOQOL_health_qol 0.0631 0.0353 1.7871 172.9118 0.0757 1.0651 0.9939 1.1414
## 27 WHO_money 0.0271 0.0272 0.9964 175.6697 0.3204 1.0275 0.9741 1.0837
## 28 Socsupp_mean 0.0288 0.0344 0.8394 155.6949 0.4025 1.0292 0.9621 1.1010
## 29 Social_network_index 0.0002 0.0197 0.0086 178.5648 0.9932 1.0002 0.9623 1.0396
## 30 Soc_part_freq 0.0695 0.0438 1.5855 161.6031 0.1148 1.0720 0.9838 1.1681
## 31 Soc_part_types -0.0153 0.0193 -0.7958 164.2810 0.4273 0.9848 0.9483 1.0228
## 32 Lonely_bin -0.0044 0.0751 -0.0585 148.1629 0.9534 0.9956 0.8593 1.1535
## 33 Motivate_mean -0.0059 0.0292 -0.2026 179.3079 0.8397 0.9941 0.9388 1.0527## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -1.2882 0.4977 -2.5882 122.9981 0.0108 0.2758 0.1040 0.7315
## 2 Gender_bin 0.1151 0.0557 2.0671 196.7062 0.0400 1.1220 1.0059 1.2514
## 3 Age 0.0067 0.0036 1.8643 239.4622 0.0635 1.0067 0.9996 1.0139
## 4 Retired_bin -0.0494 0.0519 -0.9516 248.3566 0.3422 0.9518 0.8597 1.0537
## 5 Volunteer_rec 0.0371 0.0302 1.2278 244.5447 0.2207 1.0378 0.9782 1.1011
## 6 Lives_alone_bin 0.0762 0.0609 1.2519 209.9147 0.2120 1.0792 0.9578 1.2160
## 7 Phys_health_rating 0.0279 0.0380 0.7341 154.8735 0.4640 1.0283 0.9545 1.1078
## 8 Multimorbidity_score -0.0054 0.0097 -0.5506 252.4999 0.5824 0.9946 0.9759 1.0137
## 9 Mobility_needs_bin 0.0265 0.1215 0.2178 114.6821 0.8280 1.0269 0.8093 1.3030
## 10 ABC_mean -0.0021 0.0021 -1.0394 165.3739 0.3001 0.9979 0.9938 1.0020
## 11 Subj_vision_rating_aided 0.0013 0.0326 0.0402 248.4262 0.9680 1.0013 0.9393 1.0674
## 12 Subj_hearing_loss_bin 0.0739 0.0719 1.0273 170.9803 0.3057 1.0767 0.9352 1.2396
## 13 Subj_hearing_rating_unaided_REV 0.1157 0.0348 3.3203 252.0340 0.0010 1.1227 1.0486 1.2019
## 14 Tinnitus_past_wk_bin -0.0472 0.0475 -0.9927 249.0090 0.3218 0.9539 0.8691 1.0470
## 15 PTA4_better_ear 0.0066 0.0031 2.1441 93.3090 0.0346 1.0066 1.0005 1.0128
## 16 PTA4_asym 0.0018 0.0021 0.8423 112.5263 0.4014 1.0018 0.9977 1.0059
## 17 SSQ15i_mean_REV -0.1002 0.0187 -5.3719 177.3916 0.0000 0.9047 0.8721 0.9384
## 18 Emocheq_mean -0.0066 0.0293 -0.2237 163.6258 0.8233 0.9934 0.9380 1.0521
## 19 HHIES_total 0.0091 0.0040 2.2537 120.3900 0.0260 1.0091 1.0013 1.0171
## 20 SIM_mean -0.0117 0.0117 -1.0071 175.5777 0.3153 0.9884 0.9660 1.0113
## 21 positive_SCI_bin 0.0940 0.0773 1.2161 168.2063 0.2257 1.0986 0.9441 1.2783
## 22 CSRQ_mean 0.0430 0.0735 0.5850 104.3475 0.5598 1.0439 0.9039 1.2057
## 23 PHQ4_anx_sum 0.0777 0.0266 2.9170 166.8885 0.0040 1.0808 1.0259 1.1386
## 24 PHQ4_dep_sum -0.0134 0.0290 -0.4629 218.1068 0.6439 0.9867 0.9322 1.0444
## 25 WHOQOL_overall_qol 0.0869 0.0484 1.7932 208.3303 0.0744 1.0908 0.9921 1.1993
## 26 WHOQOL_health_qol 0.0135 0.0328 0.4127 168.1729 0.6804 1.0136 0.9505 1.0809
## 27 WHO_money 0.0239 0.0275 0.8685 171.4992 0.3863 1.0242 0.9704 1.0809
## 28 Socsupp_mean -0.0029 0.0395 -0.0741 63.1461 0.9411 0.9971 0.9228 1.0774
## 29 Social_network_index 0.0029 0.0211 0.1364 139.3696 0.8917 1.0029 0.9623 1.0452
## 30 Soc_part_freq -0.0405 0.0401 -1.0112 165.2686 0.3134 0.9603 0.8877 1.0388
## 31 Soc_part_types 0.0019 0.0190 0.1000 124.3464 0.9205 1.0019 0.9653 1.0399
## 32 Lonely_bin -0.0338 0.0690 -0.4899 152.5273 0.6249 0.9668 0.8445 1.1068
## 33 Motivate_mean 0.0204 0.0309 0.6608 77.3440 0.5107 1.0206 0.9606 1.0843Legend: Asterisks denote p < 0.05; crosses denote p [0.05, 0.1]
Variable selection: Predicting HA adoption
Penalized logistic regression (LASSO) with 5-fold cross-validation was conducted across 100 lambda (penalty) values. The lambda value that led to the best-fitting model (with lowest cross-validation error) was 0.044, which corresponds to a model with 13 predictors:
Regression output (13 selected) (imputed data, n=525)
## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -0.7963 0.1793 -4.4423 466.5515 0.0000 0.4510 0.3174 0.6409
## 2 Gender_bin 0.0355 0.0325 1.0917 489.3016 0.2755 1.0361 0.9722 1.1043
## 3 Age 0.0022 0.0022 1.0205 290.7249 0.3083 1.0022 0.9979 1.0065
## 4 Volunteer_rec 0.0421 0.0182 2.3067 472.5371 0.0215 1.0430 1.0064 1.0809
## 5 Lives_alone_bin -0.0225 0.0390 -0.5760 497.0567 0.5649 0.9778 0.9058 1.0554
## 6 Subj_hearing_loss_bin 0.0784 0.0482 1.6269 292.9549 0.1048 1.0816 0.9841 1.1887
## 7 Subj_hearing_rating_unaided_REV 0.0945 0.0244 3.8755 431.6994 0.0001 1.0991 1.0478 1.1530
## 8 PTA4_better_ear 0.0083 0.0023 3.6810 67.2129 0.0005 1.0083 1.0038 1.0129
## 9 PTA4_asym 0.0031 0.0014 2.1174 138.5066 0.0360 1.0031 1.0004 1.0059
## 10 SSQ15i_mean_REV -0.0749 0.0123 -6.0967 272.3709 0.0000 0.9278 0.9057 0.9505
## 11 HHIES_total 0.0054 0.0025 2.1303 169.9426 0.0346 1.0054 1.0005 1.0104
## 12 PHQ4_anx_sum 0.0480 0.0146 3.2757 187.7804 0.0013 1.0492 1.0196 1.0796
## 13 WHO_money 0.0381 0.0178 2.1395 215.4898 0.0335 1.0388 1.0032 1.0757
## 14 Socsupp_mean 0.0268 0.0208 1.2879 333.0934 0.1987 1.0272 0.9861 1.0699Limiting the model to the 8 predictors with p < 0.05, all 8 predictors remain significant in a standard logistic regression model.
Regression output (8 selected) (imputed data, n=525)
## Term Estimate StdError t df p OddsRatio CIlower CIupper
## 1 (Intercept) -0.6127 0.1044 -5.8707 218.5124 0.0000 0.5419 0.4416 0.6649
## 2 Volunteer_rec 0.0421 0.0181 2.3210 428.5667 0.0208 1.0430 1.0066 1.0807
## 3 Subj_hearing_rating_unaided_REV 0.1115 0.0225 4.9617 379.4792 0.0000 1.1180 1.0697 1.1684
## 4 PTA4_better_ear 0.0104 0.0018 5.6517 192.1114 0.0000 1.0105 1.0069 1.0140
## 5 PTA4_asym 0.0034 0.0014 2.4128 206.3060 0.0167 1.0034 1.0007 1.0062
## 6 SSQ15i_mean_REV -0.0755 0.0123 -6.1393 279.6360 0.0000 0.9273 0.9052 0.9499
## 7 HHIES_total 0.0054 0.0025 2.1268 130.9653 0.0353 1.0054 1.0005 1.0104
## 8 PHQ4_anx_sum 0.0418 0.0145 2.8772 157.7745 0.0046 1.0427 1.0135 1.0727
## 9 WHO_money 0.0509 0.0170 2.9949 226.0709 0.0031 1.0522 1.0177 1.0879
Accuracy of model predictions
## [1] "Imputed data, 8 predictors, using median as boundary to classify 0 or 1"## predicted
## actual 0 1
## 0 252 170
## 1 11 92## [1] "Accuracy: 0.655"## [1] "Sensitivity: 0.893"## [1] "Specificity: 0.597"ROC: BPTA4 and HA adoption
Complete cases only (n=449)
Imputed data (n=525)
## m best_threshold sensitivity specificity auc
## 1 1 26.875 0.7087379 0.7654028 0.7811278
## 2 2 26.875 0.6796117 0.7464455 0.7694980
## 3 3 26.875 0.6796117 0.7630332 0.7762849
## 4 4 26.875 0.6990291 0.7677725 0.7731445
## 5 5 25.625 0.7087379 0.7085308 0.7640800
ROC: HHIES and HA adoption
Complete cases only (n=512)
Imputed data (n=525)
## m best_threshold sensitivity specificity auc
## 1 1 9 0.7475728 0.563981 0.6803249
## 2 2 9 0.7378641 0.563981 0.6737680
## 3 3 9 0.7378641 0.5687204 0.6774375
## 4 4 9 0.7475728 0.5687204 0.6821539
## 5 5 9 0.7378641 0.563981 0.6734574
ROC: SSQ-15i and HA adoption
Complete cases only (n=455)
Imputed data (n=525)
## m best_threshold sensitivity specificity auc
## 1 1 2.156667 0.6893204 0.3838863 0.5199351
## 2 2 2.156667 0.6990291 0.3767773 0.5222128
## 3 3 1.886667 0.631068 0.4336493 0.5233516
## 4 4 2.156667 0.6893204 0.3815166 0.5196475
## 5 5 2.156667 0.7087379 0.3838863 0.5267450
4. Special populations
The standard relationship, HA ~ BPTA4
Plots showing thresholds for BPTA4, Asymmetry, HHIES
- Of the three, BPTA4 is the best standalone predictor of HA
adoption.
- Legend: Red = HA adopters. Lines are thresholds for highest area-under-curve. Complete cases only, n=423.
Comparing three predictors: BPTA4, Asymmetry, HHIES
- On their own, BPTA4 and HHIES help predict HA adoption. On its own,
PTA4 asymmetry doesn’t.
- When BPTA4 is the main predictor, adding HHIES doesn’t help predict HA adoption, while adding PTA4 asymmetry does help a little.
## Analysis of Deviance Table
##
## Model 1: study2_HA ~ 1
## Model 2: study2_HA ~ BPTA4
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 422 413.17
## 2 421 336.89 1 76.272 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: study2_HA ~ 1
## Model 2: study2_HA ~ PTA4_asym
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 422 413.17
## 2 421 409.65 1 3.5179 0.06071 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: study2_HA ~ 1
## Model 2: study2_HA ~ HHIES_total
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 422 413.17
## 2 421 392.72 1 20.448 0.000006129 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1## Analysis of Deviance Table
##
## Model 1: study2_HA ~ BPTA4
## Model 2: study2_HA ~ BPTA4 + PTA4_asym
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 421 336.89
## 2 420 331.60 1 5.2977 0.02135 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## glm(formula = study2_HA ~ BPTA4 + PTA4_asym, family = "binomial",
## data = compdata)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.617386 0.470057 -9.823 < 2e-16 ***
## BPTA4 0.119007 0.015530 7.663 0.0000000000000182 ***
## PTA4_asym 0.022451 0.009219 2.435 0.0149 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 413.17 on 422 degrees of freedom
## Residual deviance: 331.60 on 420 degrees of freedom
## AIC: 337.6
##
## Number of Fisher Scoring iterations: 5## Analysis of Deviance Table
##
## Model 1: study2_HA ~ BPTA4
## Model 2: study2_HA ~ BPTA4 + HHIES_total
## Resid. Df Resid. Dev Df Deviance Pr(>Chi)
## 1 421 336.89
## 2 420 333.79 1 3.1032 0.07814 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1##
## Call:
## glm(formula = study2_HA ~ BPTA4 + HHIES_total, family = "binomial",
## data = compdata)
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.52791 0.46182 -9.804 < 2e-16 ***
## BPTA4 0.10849 0.01569 6.915 0.00000000000469 ***
## HHIES_total 0.02771 0.01568 1.768 0.0771 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 413.17 on 422 degrees of freedom
## Residual deviance: 333.79 on 420 degrees of freedom
## AIC: 339.79
##
## Number of Fisher Scoring iterations: 5“Red flag” variables
Using BPTA4 as the standalone predictor of HA adoption, the sample can be divided into four groups:
## predicted HA
## actual HA 0 1
## 0 280 85
## 1 23 61The plot below shows potential “red flag” variables, and which individual participants have them within each group.
Continuous and ordinal variables have been dichotomized according to
these cut-offs:
* PTA4 asymmetry ≥ 20 dB HL
* HHIES ≥ 10
* PHQ4 subscores ≥ 3
* Social participation of less than once per week in any activity
* Mean social support of less than “some of the time” (< 2.5 out of 5
on average)
* Generally, any WHOQOL-BREF responses that are in the worst 2 of 5
categories. There are a few exceptions, where it’s clear that the worst
3 categories are red flags according to the distribution (physical pain,
medical treatment, money, information, getting around, health services,
transport, negative mood).
Counts of participants experiencing each red flag
## [1] "Test of proportions conducted for first two columns: HA expected and nonHA unexpected"## [1] "Test of proportions generally requires 5 positive cases per group"## Variable HA_exp nonHA_unexp nonHA_exp HA_unexp chisq pvalue
## 1 Asymmetry_bin 2 5 8 4 0.1112 0.7387
## 2 HHIES_bin 42 46 95 16 2.6342 0.1046
## 3 Tinnitus_past_wk_bin 15 35 82 10 3.6334 0.0566
## 4 Mobility_needs_bin 5 4 14 1 0.2664 0.6058
## 5 Poor_aided_vision_bin 3 1 8 0 0.7258 0.3942
## 6 positive_SCI_bin 7 11 25 4 0.0001 0.9916
## 7 PHQ4_anx_bin 26 23 100 11 3.1917 0.0740
## 8 PHQ4_dep_bin 11 23 74 7 1.1537 0.2828
## 9 Lonely_bin 9 19 52 7 0.8782 0.3487
## 10 MOS_socsupp_bin 3 11 10 4 1.7926 0.1806
## 11 CCHS_socpartfreq_bin 2 4 13 2 0.0000 0.9954
## 12 WHO_qol_bin 4 4 5 0 0.0135 0.9075
## 13 WHO_health_satisf_bin 7 16 32 4 0.9442 0.3312
## 14 WHO_phys_pain_bin 9 21 57 5 1.5879 0.2076
## 15 WHO_med_treatment_bin 8 18 51 2 1.0742 0.3000
## 16 WHO_enjoy_life_bin 1 5 5 1 0.7244 0.3947
## 17 WHO_meaningful_bin 3 6 11 0 0.0330 0.8559
## 18 WHO_concentrate_bin 2 3 6 1 0.0000 1.0000
## 19 WHO_feel_safe_bin 1 2 3 0 0.0000 1.0000
## 20 WHO_healthy_env_bin 2 1 1 0 0.0851 0.7705
## 21 WHO_energy_bin 3 6 13 2 0.0330 0.8559
## 22 WHO_body_appear_bin 2 7 14 2 0.7732 0.3792
## 23 WHO_money_bin 8 22 41 4 2.8071 0.0938
## 24 WHO_information_bin 5 6 11 0 0.0000 1.0000
## 25 WHO_leisure_bin 1 7 13 2 1.8456 0.1743
## 26 WHO_get_around_bin 2 5 11 2 0.1112 0.7387
## 27 WHO_sleep_satisf_bin 11 21 57 8 0.5753 0.4482
## 28 WHO_ability_ADL_bin 3 5 12 0 0.0000 1.0000
## 29 WHO_capacity_work_bin 4 5 21 1 0.0000 1.0000
## 30 WHO_satisf_self_bin 2 6 16 2 0.3859 0.5345
## 31 WHO_satisf_relat_bin 2 11 12 2 2.9833 0.0841
## 32 WHO_satisf_sex_bin 13 19 60 4 0.0000 1.0000
## 33 WHO_satisf_support_bin 1 4 9 1 0.2954 0.5868
## 34 WHO_living_place_bin 4 6 8 3 0.0000 1.0000
## 35 WHO_access_health_bin 6 10 39 3 0.0099 0.9209
## 36 WHO_transport_bin 0 3 13 3 0.7942 0.3728
## 37 WHO_neg_feelings_bin 9 15 45 4 0.0570 0.8113
## 38 Motiv_convers_bin 9 8 25 0 0.5343 0.4648
## 39 Motiv_lect_bin 11 15 34 2 0.0000 1.0000
## 40 Motiv_tvradmu_bin 9 17 26 2 0.3574 0.5500
## 41 Motiv_family_bin 5 8 12 0 0.0000 1.0000
## 42 Motiv_friends_bin 11 9 12 1 1.0947 0.2954
## 43 Motiv_social_bin 12 7 22 1 3.1554 0.0757
## 44 Motiv_sadfrus_bin 14 12 23 5 1.3377 0.2474
## 45 Motiv_fatigue_bin 20 19 38 2 1.4779 0.2241
## 46 Motiv_health_bin 15 22 43 5 0.0000 1.0000
## 47 Motiv_cogn_bin 14 19 27 4 0.0000 1.0000Percentages of participants experiencing each red flag
## [1] "Test of proportions conducted for first two columns: HA expected and nonHA unexpected"## [1] "Test of proportions generally requires 5 positive cases per group"## Variable HA_exp_p nonHA_unexp_p nonHA_exp_p HA_unexp_p chisq pvalue
## 1 Asymmetry_bin 3.3 5.9 2.9 17.4 0.1112 0.7387
## 2 HHIES_bin 68.9 54.1 33.9 69.6 2.6342 0.1046
## 3 Tinnitus_past_wk_bin 24.6 41.2 29.3 43.5 3.6334 0.0566
## 4 Mobility_needs_bin 8.2 4.7 5.0 4.3 0.2664 0.6058
## 5 Poor_aided_vision_bin 4.9 1.2 2.9 0.0 0.7258 0.3942
## 6 positive_SCI_bin 11.5 12.9 8.9 17.4 0.0001 0.9916
## 7 PHQ4_anx_bin 42.6 27.1 35.7 47.8 3.1917 0.0740
## 8 PHQ4_dep_bin 18.0 27.1 26.4 30.4 1.1537 0.2828
## 9 Lonely_bin 14.8 22.4 18.6 30.4 0.8782 0.3487
## 10 MOS_socsupp_bin 4.9 12.9 3.6 17.4 1.7926 0.1806
## 11 CCHS_socpartfreq_bin 3.3 4.7 4.6 8.7 0.0000 0.9954
## 12 WHO_qol_bin 6.6 4.7 1.8 0.0 0.0135 0.9075
## 13 WHO_health_satisf_bin 11.5 18.8 11.4 17.4 0.9442 0.3312
## 14 WHO_phys_pain_bin 14.8 24.7 20.4 21.7 1.5879 0.2076
## 15 WHO_med_treatment_bin 13.1 21.2 18.2 8.7 1.0742 0.3000
## 16 WHO_enjoy_life_bin 1.6 5.9 1.8 4.3 0.7244 0.3947
## 17 WHO_meaningful_bin 4.9 7.1 3.9 0.0 0.0330 0.8559
## 18 WHO_concentrate_bin 3.3 3.5 2.1 4.3 0.0000 1.0000
## 19 WHO_feel_safe_bin 1.6 2.4 1.1 0.0 0.0000 1.0000
## 20 WHO_healthy_env_bin 3.3 1.2 0.4 0.0 0.0851 0.7705
## 21 WHO_energy_bin 4.9 7.1 4.6 8.7 0.0330 0.8559
## 22 WHO_body_appear_bin 3.3 8.2 5.0 8.7 0.7732 0.3792
## 23 WHO_money_bin 13.1 25.9 14.6 17.4 2.8071 0.0938
## 24 WHO_information_bin 8.2 7.1 3.9 0.0 0.0000 1.0000
## 25 WHO_leisure_bin 1.6 8.2 4.6 8.7 1.8456 0.1743
## 26 WHO_get_around_bin 3.3 5.9 3.9 8.7 0.1112 0.7387
## 27 WHO_sleep_satisf_bin 18.0 24.7 20.4 34.8 0.5753 0.4482
## 28 WHO_ability_ADL_bin 4.9 5.9 4.3 0.0 0.0000 1.0000
## 29 WHO_capacity_work_bin 6.6 5.9 7.5 4.3 0.0000 1.0000
## 30 WHO_satisf_self_bin 3.3 7.1 5.7 8.7 0.3859 0.5345
## 31 WHO_satisf_relat_bin 3.3 12.9 4.3 8.7 2.9833 0.0841
## 32 WHO_satisf_sex_bin 21.3 22.4 21.4 17.4 0.0000 1.0000
## 33 WHO_satisf_support_bin 1.6 4.7 3.2 4.3 0.2954 0.5868
## 34 WHO_living_place_bin 6.6 7.1 2.9 13.0 0.0000 1.0000
## 35 WHO_access_health_bin 9.8 11.8 13.9 13.0 0.0099 0.9209
## 36 WHO_transport_bin 0.0 3.5 4.6 13.0 0.7942 0.3728
## 37 WHO_neg_feelings_bin 14.8 17.6 16.1 17.4 0.0570 0.8113
## 38 Motiv_convers_bin 14.8 9.4 8.9 0.0 0.5343 0.4648
## 39 Motiv_lect_bin 18.0 17.6 12.1 8.7 0.0000 1.0000
## 40 Motiv_tvradmu_bin 14.8 20.0 9.3 8.7 0.3574 0.5500
## 41 Motiv_family_bin 8.2 9.4 4.3 0.0 0.0000 1.0000
## 42 Motiv_friends_bin 18.0 10.6 4.3 4.3 1.0947 0.2954
## 43 Motiv_social_bin 19.7 8.2 7.9 4.3 3.1554 0.0757
## 44 Motiv_sadfrus_bin 23.0 14.1 8.2 21.7 1.3377 0.2474
## 45 Motiv_fatigue_bin 32.8 22.4 13.6 8.7 1.4779 0.2241
## 46 Motiv_health_bin 24.6 25.9 15.4 21.7 0.0000 1.0000
## 47 Motiv_cogn_bin 23.0 22.4 9.6 17.4 0.0000 1.0000